Endocrine fertility traits, which are defined from progesterone concentration levels in milk, are interesting indicators of dairy cow fertility because they more directly reflect the cows own reproductive physiology than classical fertility traits, which are more biased by farm management decisions. The aim of this study was to detect quantitative trait loci (QTL) for 7 endocrine fertility traits in dairy cows by performing a genome-wide association study with 85k SNP, and then fine-map targeted QTL regions, using imputed sequence variants. Two classical fertility traits were also analyzed for QTL with 85k SNP. The association between a SNP and a phenotype was assessed by single-locus regression for each SNP, using a linear mixed model that included a random polygenic effect. A total of 2,447 Holstein Friesian cows with 5,339 lactations with both phenotypes and genotypes were used for association analysis. Heritability estimates ranged from 0.09 to 0.15 for endocrine fertility traits and 0.03 to 0.10 for classical fertility traits. The genome-wide association study identified 17 QTL regions for endocrine fertility traits on Bos taurus autosomes (BTA) 2, 3, 8, 12, 15, 17, 23, and 25. The highest number (5) of QTL regions from the genome-wide association study was identified for the endocrine trait "proportion of samples with luteal activity." Overlapping QTL regions were found between endocrine traits on BTA 2, 3, and 17. For the classical trait calving to first service, 3 QTL regions were identified on BTA 3, 15, and 23, and an overlapping region was identified on BTA 23 with endocrine traits. Fine-mapping target regions for the endocrine traits on BTA 2 and 3 using imputed sequence variants confirmed the QTL from the genome-wide association study, and identified several associated variants that can contribute to an index of markers for genetic improvement of fertility. Several potential candidate genes underlying endocrine fertility traits were also identified in the target regions and are discussed. However, due to high linkage disequilibrium, it was not possible to specify genes or polymorphisms as causal factors for any of the regions.